An introduction
to the monitoring of
forestry carbon sequestration
projects
Igino M. Emmer PhD
Face Foundation
Developing Forestry and Bioenergy Projects within CDM
Ecuador
March, 2004
F orests
A bsorbing
C arbon dioxide
E mission
Overview of the Face projects
The Netherlands
area: 5.000 ha
start: March 1992
Czech-Republic
KRNAP/NPS
area: 14.000 ha
start: October 1992
Sabah-Malaysia
Infapro
area: 14.000 ha
start: July 1992
Ecuador
Profafor
area: 75.000 ha
start: June 1993
Uganda
UNP-Face
area: 27.000 ha
start: August 1994
Contents
• Introduction
• Basic principles of carbon monitoring in forests
Introduction
What is carbon monitoring in forests?
Forest carbon monitoring quantifies
changes in carbon stocks in various
carbon pools of the forest
by repeated measurement
Why carbon monitoring?
- Transparency and credibility
- Verification (see project cycle)
- Compliance versus voluntary
• COP 9
• IPCC GPG LULUCF
• Large versus small-scale projects
Monitoring plan
• Contents (CDM EB):
- GHG baseline and with-project
- Archiving
- Nature and quality of methodologies
- Remedial measures for negative impacts
• This introduction: carbon monitoring in
CDM AR
Good Practice
• Intergovernmental Panel on Climate
Change Good Practice Guidance for Land
Use, Land Use Change and Forestry
- Revised 1996 IPCC Guidelines for
National Greenhouse Gas Inventories
- National inventories and projects
• Winrock International and others
Basic principles of carbon monitoring
• First considerations for planning
• Data requirements
• Tools for data collection
• Carbon calculations
• Leakage, risks and uncertainties
First considerations for planning
• Greenhouse gasses involved
• Baseline versus with-project scenario
• Required frequency
• Availability of expertise
• Costs
Greenhouse gasses involved
• CO2
(1 CO2e)
• CH4
(23 CO2e)
• N2O
(296 CO2e)
Baseline versus with-project scenario
• Baseline may become counterfactual
• Plot selection
• Modelling
Required frequency
• Lomax: lowest cost/effort, maximum result
• Carbon monitoring vs research
• CDM AR: 5-year intervals
• Just before verification
• Statistics
- Stock changes versus variability
Stock changes versus variability
Carbon content (unit)
High variability + small average change:
large sample size
2002
2012
Measurement year
Pre-defined precision and accuracy
• Precision: e.g. measuring a stem diameter
• Accuracy: assessing the carbon stored in the
forest
Can be found in the IPCC GPG LULUCF
Availability of expertise: fields
• Forestry, terrain knowledge
• Sampling design and statistics
• Logistics
• Supervision and quality control
Costs
• Labour intensive, time consuming:
may easily become expensive
• Lomax
- Pre-monitoring intelligence
- Pilot sampling
• Relation with market price of CO2e
(end of considerations)
Data requirement
• 50% of biomass is carbon (C)
• Carbon pools
- Above-ground biomass
- Below-ground biomass
- Soil carbon
- Litter
Pools to be involved
• In principle all carbon pools within the
project boundary must be considered
• Only if transparent and verifiable
information is provided, pools that are
shown not to be a source may be excluded
from the monitoring
Above-ground biomass
1.3 m
1.3 m
st
1 diameter
nd
2 diameter
1.3 m
1.3 m
1.3 m
two measurements
1.3 m
1.3 m
Above-ground biomass
allometric biomass regression equation:
B = a + b * D2 * H
where
B: biomass (kg)
D: stem diameter (cm) at breast height (1.3 m)
H: total height (m)
a-b: regression parameters from the data,
depending on tree species and site conditions
Below-ground biomass
• Average below-ground to above-ground ratio for
tropical, boreal and temperate forest (IPCC) = 0.26
• Varying little among latitudes (boreal-temperatetropical) or soil texture
• IPCC guidelines: ‘given the lack of standard methods
and the time-consuming nature of monitoring belowground biomass in forests, it is good practice to
estimate below-ground biomass from either estimated
aboveground biomass based on various equations or
from locally derived data’
Soil carbon
A general formula for calculating soil organic carbon:
SOC = [SOC] * BulkDensity * Volume * (1-CoarsFragments)
where
SOC: soil carbon stock (Mg C/ha)
[SOC]: concentration of soil carbon (g C/kg)
BulkDensity (Mg/m3)
CoarseFragments: fraction in %
Tools for data collection
Good monitoring depends on
• An adequate land classification scheme
• An appropriate spatial and temporal resolution
• A proper standard for precision and accuracy
• A transparent methodology
• Measures to assure consistency and availability over
time
Remote sensing
• Air photography
• Satellite imagery
• Radar
Ground-based surveys; sampling design
• Ground-based surveys require field visits for
measuring selected attributes
• The way these attributes are measured in terms of
‘how many times’ and ‘where’ is the sampling
design
• The sampling design must
- prevent any bias in measurements
- allow for efficient execution of the work
- allow for independent verification
Sampling design
• Complete enumeration
• Simple random sampling
• Systematic sampling
• Stratified random sampling
Precision, Accuracy, Lomax
Sampling unit
• Plot (permanent or temporary)
• Pre-defined constant area (tonnes C/ha)
• Permanent plots:
- Better quantification of stock changes
- Independent verification
Sample grid
Sample size versus precision level
Equipment
Carbon calculations
• Carbon stocks
• Sample size
• Time intervals
Other issues
• Leakage
- Monitoring within project boundaries
• Risks and uncertainties
- Assessment
- Mitigation